TY - CONF
T1 - Applications of Voting Theory to Information Mashups
T2 - 2nd IEEE International Conference on Semantic Computing
Y1 - 2008
A1 - Christine Robson
A1 - Jan Pieper
A1 - Nachiketa Sahoo
A1 - Alfredo Alba
A1 - Meenakshi Nagarajan
A1 - Daniel Gruhl
A1 - Varun Bhagwan
A1 - Julia Grace
A1 - Kevin Haas
AB - Blogs, discussion forums and social networking sites are an excellent source for people's opinions on a wide range of topics. We examine the application of voting theory to 'Information Mashups' - the combining and summarizing of data from the multitude of often-conflicting sources. This paper presents an information mashup in the music domain: a Top 10 artist chart based on user comments and listening behavior from several Web communities. We consider different voting systems as algorithms to combine opinions from multiple sources and evaluate their effectiveness using social welfare functions. Different voting schemes are found to work better in some applications than others. We observe a tradeoff between broad popularity of established artists versus emerging superstars that may only be popular in one community. Overall, we find that voting theory provides a solid foundation for information mashups in this domain.
JA - 2nd IEEE International Conference on Semantic Computing
CY - Santa Clara, CA, USA
ER -